System for monitoring a switchgear

ABSTRACT

A system for monitoring a switchgear includes: an infrared camera for acquiring at least one infrared image of the switchgear; a processing unit for determining a pixel in the at least one infrared image associated with a hottest temperature, determining e pixels in the at least one infrared image associated with a temperature that is within a threshold temperature of the hottest temperature, and determining that a hot spot exists in the switchgear as a determination, the determination being a utilization of the determined pixels in the at least one infrared image; and an output unit for outputting an indication of a fault in the switchgear based on the determined hot spot.

CROSS-REFERENCE TO PRIOR APPLICATION

Priority is claimed to European Patent Application No. EP 19 194 696.1,filed on Aug. 30, 2019, the entire disclosure of which is herebyincorporated by reference herein.

FIELD

The present invention relates to a system for monitoring a switchgear.

BACKGROUND

Infrared (IR) images can be used to identify technical problems withinelectrical equipment (e.g. switchgear) that leads to overheating ofcomponents. However, while a human is quite capable of recognizing hotspots, automated systems require specific configurations to be ableproperly to recognize the problems. A typical approach is to identify aregion of interest for each phase. These regions can then be compared.If one is significantly hotter than the others, a fault has occurred.

There are several drawbacks to this approach. First of all, the phaseshave to be identified in the IR image manually for each model and ratingof switchgear. This is a time consuming, expensive and error-proneprocess as the exact position of the phases in the IR image depend onmany switchgear specific parameters (panel size, current rating,internal structure) as well as camera specific parameters (field ofview, resolution, and manufacturing tolerances of optics). Second, anyhot activity outside the defined region of interest will be ignored, soany mistakes reduce the efficiency of the algorithm, and any developingproblem in a different component will not be detected. Thirdly, amodification of the switchgear during a service task in the field mayinfluence the identification of phases in the IR image, and/or anymovement or change in alignment of the camera's field of view leads to achange of the position of the regions and to incorrect operation.

There is a need to address these issues.

SUMMARY

In an embodiment, the present invention provides a system for monitoringa switchgear, the system comprising: an infrared camera configured toacquire at least one infrared image of the switchgear; a processing unitconfigured to determine a pixel in the at least one infrared imageassociated with a hottest temperature, to determine pixels in the atleast one infrared image associated with a temperature that is within athreshold temperature of the hottest temperature, and to determine thata hot spot exists in the switchgear as a determination, thedetermination comprising a utilization of the determined pixels in theat least one infrared image; and an output unit configured to output anindication of a fault in the switchgear based on the determined hotspot.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be described in even greater detail belowbased on the exemplary figures. The invention is not limited to theexemplary embodiments. Other features and advantages of variousembodiments of the present invention will become apparent by reading thefollowing detailed description with reference to the attached drawingswhich illustrate the following:

FIG. 1 shows a detailed workflow relating to an example of theprocessing undertaken to determine a fault in a switchgear;

FIG. 2 shows the number of pixels in an image for examples of normal andfaulty situations; and

FIG. 3 shows can example of the maximum temperatures for a normalsituation with two normally operating components on the right and showson the left the processed image when the left hand component hassuffered a fault.

DETAILED DESCRIPTION

In an embodiment, the present invention provides an improved system forprocessing the IR image of electrical equipment to actionableinformation.

It is to be noted that the system is described with respect to aswitchgear, but finds utility in other electrical system than can sufferfrom components that overheat.

In an aspect, there is provided a system for monitoring a switchgear.The system comprises:

an infrared camera;

a processing unit: and

an output unit.

The infrared camera is configured to acquire at least one infrared imageof the switchgear. The processing unit is configured to determine apixel in the at least one infrared image associated with a hottesttemperature. The processing unit is configured to determine pixels inthe at least one infrared image associated with a temperature that iswithin a threshold temperature of the hottest temperature. Theprocessing unit is configured to determine that a hot spot exists in theswitchgear, the determination comprising utilization of the determinedpixels in the at least one infrared image. The output unit is configuredto output an indication of a fault in the switchgear on the basis of thedetermined hot spot.

In this way, knowledge of the structure of the switchgear andidentification of those areas that could suffer from hot spots is notrequired, rather a determination of any regions that are hot is made.The shape, size, position, and number of the hot regions and how theyare or are not joined can be used to determine if there is a hot spotindicative of a fault.

It is to be noted that an infrared image also means a thermogram, witharrays of numbers representing temperatures measured by each pixel ofthe camera.

In an example, the threshold temperature is a fixed temperature range.

In an example, the at least one image comprises a first infrared imageand a second infrared image acquired after the first infrared image. Theprocessing unit is configured to determine a pixel in the first infraredimage associated with a hottest temperature of the first infrared imageand determine a pixel in the second infrared image associated with ahottest temperature of the second infrared image. The processing unit isconfigured to determine pixels in the first infrared image associatedwith a temperature that is within the threshold temperature of thehottest temperature in the first infrared image and determine pixels inthe second infrared image associated with a temperature that is withinthe threshold temperature of the hottest temperature in the secondinfrared image. The processing unit is configured to determine that thehot spot exists in the switchgear comprising a comparison of thedetermined pixels in the first infrared image with the determines pixelsin the second infrared image.

Thus, for example a change in size of the hottest region can indicate afault. As a part becomes hotter it has been found that the size of theregion within a set temperature range of the hottest pixel can actuallybecome smaller, and this reduction in size can be used to determine thata fault has developed. Also, a number of separate hot spot regions in afirst image can be indicative of a number of similar or same componentsoperating normally where they are heating up due to Joule heating.However, if one component develops a fault and becomes hot the hottesttemperature range can then be centred around only the hottest part ofthat component, and the hot regions of the other components are thenoutside of this threshold range. Thus, a reduction in the number ofseparate regions from an image to a subsequent image can be used toindicate that the region in the subsequent image has a fault. A changein shape if the hot region can also be used to indicate that there isnow a fault.

In an example, the determination that the hot spot exists comprises ananalysis of one or more of: a shape of at least one region within thedetermined pixels in the at least one infrared image; a size of the atleast one region within the determined pixels in the at least oneinfrared image; a position of the at least one region within thedetermined pixels in the at least one infrared image; a number of the atleast one region within the determined pixels in the at least oneinfrared image; a number of pixels within the determined pixels in theat least one infrared image.

In an example, the determination that the hot spot exists comprises adetermination that a region in the second infrared image is smaller thana corresponding region in the first infrared image.

In an example, the determination that the hot spot exists comprises adetermination that a number of regions in the second infrared image issmaller than a number of regions in the first infrared image.

In an example, the determination that the hot spot exists comprises adetermination that the number of regions in the second image is one.

In an example, the switchgear comprises two or more components of thesame type that are loaded with substantially the same current. Thedetermination that the hot spot exists comprises a determination of oneor more of: a shape of a first region within the determined pixels inthe at least one infrared image is different to a shape of a secondregion within the determined pixels in the at least one infrared image;a size of a first region within the determined pixels in the at leastone infrared image is different to a size of a second region within thedetermined pixels in the at least one infrared image; a position aregion within the determined pixels in the at least one infrared imageis not associated with a position of the two or more components; anumber of the at least one region within the determined pixels in the atleast one infrared image is less than a number of the two or morecomponents.

In other words, when it is knows that there are for example threecurrent carrying components, such as the three poles of 3-phase circuitbreakers, that should equally be hot, then normally there should bethree separate hot regions within the threshold temperature range of thehottest pixel. However, when one of these components develops a faultand becomes hot, then when the threshold temperature range is correctlyselected then the maximum temperatures of the other components sitoutside of the maximum temperatures (within the temperature range of thehottest temperature) of the faulty component. A consequence is thatthere is only one region of temperature within the hottest temperatures,rather than three in this example, and this can be used to determinethat the component that has this hottest temperature has a fault.

In an example, the determination that the hot spot exists comprises adetermination that there is only one region within the determined pixelsin the at least one infrared image.

In an example, the determination that the hot spot exists comprises ageneration of at least one binary image. The determined pixels in the atleast one infrared image are given a different binary value to theremaining pixels in the at least one infrared image.

In this manner, a binary image can facilitate processing by a machinelearning algorithm for example.

In an example, the determination that the hot spot exists comprisesutilization of a machine learning algorithm

In an example, the machine learning algorithm is a trained neuralnetwork.

In an example, the system comprises a visible camera configured toacquire a visible image of the switchgear. The processing unit isconfigured to overlay the determined pixels in the at least one infraredimage onto corresponding at least one location in the visible image.

In other words, the location of hot pixels can be mapped to a visibleimage in order to allow a human to review the situation to determine ifthere is a fault.

In an example, the at least one image comprises a plurality of imagesacquired at different times. The processing unit is configured todetermine a pixel in each of the plurality of infrared images associatedwith a hottest temperature in each of the plurality of infrared images.The processing unit is configured to determine a number of thresholdpixels in each of the plurality of infrared images associated with atemperature that is within the threshold temperature of the hottesttemperature in each of the plurality of infrared images. Thedetermination that the hot spot exists comprises a determination of arate of change of the number of threshold pixels with time.

In an example, the determination that the hot spot exists comprises acomparison of the rate of change of the number of threshold pixels withtime against a baseline rate of change of the number of threshold pixelswith time.

The above aspects and examples will become apparent from and beelucidated with reference to the embodiments described hereinafter.

FIGS. 1-3 relate to a system for monitoring a switchgear. In an example,the system comprises an infrared camera, a processing unit, and anoutput unit. The infrared camera is configured to acquire at least oneinfrared image of the switchgear. The processing unit is configured alsoto determine a pixel in the at least one infrared image associated witha hottest temperature. The processing unit is configured also todetermine pixels in the at least one infrared image associated with atemperature that is within a threshold temperature of the hottesttemperature. The processing unit is configured also to determine that ahot spot exists in the switchgear, the determination comprisingutilization of the determined pixels in the at least one infrared image.The output unit is configured to output an indication of a fault in theswitchgear on the basis of the determined hot spot.

In an example, the indication of the fault in the switchgear on thebasis of the determined hot spot comprises an output of an image of thehot spot.

In an example, the indication of the fault in the switchgear on thebasis of the determined hot spot comprises an output of an image of thehot spot identified within the at least one infrared image.

In an example, the indication of the fault in the switchgear on thebasis of the determined hot spot comprises an output of an alarm signal.

According to an example, the threshold temperature is a fixedtemperature range.

In an example, the fixed temperature range can be a fixed number ofdegrees Celsius.

In an example, the fixed temperature range can be or a percentage of thecurrent average temperature of the image.

In an example, the fixed temperature range can be a percentage of themaximum temperature of the image.

In an example, the fixed temperature range can be a dynamically changingvalue in degrees Celsius depending on the average or maximum temperatureof the image.

In an example, the fixed temperature range of the threshold is 5 C. Inan example, the fixed temperature range of the threshold is 7 C. In anexample, the fixed temperature range of the threshold is 10 C. In anexample, the fixed temperature range of the threshold is 15 C. In anexample, the fixed temperature range of the threshold is 20 C. Thus, forexample, when the threshold temperature is 7 C, then for a hottesttemperature in the infrared image of 100 C, then all pixels having atemperature of greater than 93 C are identified.

According to an example, the at least one image comprises a firstinfrared image and a second infrared image acquired after the firstinfrared image. The processing unit is configured to determine a pixelin the first infrared image associated with a hottest temperature of thefirst infrared image and determine a pixel in the second infrared imageassociated with a hottest temperature of the second infrared image. Theprocessing unit is configured also to determine pixels in the firstinfrared image associated with a temperature that is within thethreshold temperature of the hottest temperature in the first infraredimage and determine pixels in the second infrared image associated witha temperature that is within the threshold temperature of the hottesttemperature in the second infrared image. The processing unit isconfigured also to determine that the hot spot exists in the switchgearcomprising a comparison of the determined pixels in the first infraredimage with the determines pixels in the second infrared image.

According to an example, the determination that the hot spot existscomprises an analysis of one or more of: a shape of at least one regionwithin the determined pixels in the at least one infrared image; a sizeof the at least one region within the determined pixels in the at leastone infrared image; a position of the at least one region within thedetermined pixels in the at least one infrared image; a number of the atleast one region within the determined pixels in the at least oneinfrared image; a number of pixels within the determined pixels in theat least one infrared image.

According to an example, the determination that the hot spot existscomprises a determination that a region in the second infrared image issmaller than a corresponding region in the first infrared image.

According to an example, the determination that the hot spot existscomprises a determination that a number of regions in the secondinfrared image is smaller than a number of regions in the first infraredimage.

According to an example, the determination that the hot spot existscomprises a determination that the number of regions in the second imageis one.

According to an example, the switchgear comprises two or more componentsof the same type that are loaded with substantially the same current.The determination that the hot spot exists can then comprise adetermination of one or more of: a shape of a first region within thedetermined pixels in the at least one infrared image is different to ashape of a second region within the determined pixels in the at leastone infrared image; a size of a first region within the determinedpixels in the at least one infrared image is different to a size of asecond region within the determined pixels in the at least one infraredimage; a position a region within the determined pixels in the at leastone infrared image is not associated with a position of the two or morecomponents; a number of the at least one region within the determinedpixels in the at least one infrared image is less than a number of thetwo or more components.

According to an example, the determination that the hot spot exists cancomprise a determination that there is only one region within thedetermined pixels in the at least one infrared image.

According to an example, the determination that the hot spot exists cancomprise a generation of at least one binary image. The determinedpixels in the at least one infrared image are given a different binaryvalue to the remaining pixels in the at least one infrared image. Thusfor example hot pixels can be give the value 1, and all other pixelsgiven the value 0, or vice versa.

According to an example, the determination that the hot spot existscomprises utilization of a machine learning algorithm

According to an example, the machine learning algorithm is a trainedneural network.

According to an example, the system comprises a visible cameraconfigured to acquire a visible image of the switchgear. The processingunit is configured to overlay the determined pixels in the at least oneinfrared image onto corresponding at least one location in the visibleimage.

According to an example, the at least one image comprises a plurality ofimages acquired at different times. The processing unit is configured todetermine a pixel in each of the plurality of infrared images associatedwith a hottest temperature in each of the plurality of infrared images.The processing unit is configured to determine a number of thresholdpixels in each of the plurality of infrared images associated with atemperature that is within the threshold temperature of the hottesttemperature in each of the plurality of infrared images. Thedetermination that the hot spot exists comprises a determination of arate of change of the number of threshold pixels with time.

According to an example, the determination that the hot spot existscomprises a comparison of the rate of change of the number of thresholdpixels with time against a baseline rate of change of the number ofthreshold pixels with time.

Thus, a switchgear or other electrical equipment can have installed inassociation with it the above described system.

Thus, the system takes the hottest temperature of one image andidentifies all pixels within the hottest x degrees. Anything below orabove a certain pixel count or number of connected regions for a certaintemperature can be considered a fault. The location of the pixels can bemapped to a visual-light image to tell a human were the fault is ormapped to a binarized image (where all hot pixels are black and the restof the image is white) for further processing by machine learning. Thus,in effect the newly developed system turns the original fault detectiontechnique “on its head”. Instead of identifying regions and checkingwhether they are hot, it is determined which regions are hot and thenthese regions are analyzed with respect to their shape, size, number andposition and even if whether they newly appear to identify the fault.This way, empirical results can be obtained and used to definethresholds or to use as input for machine learning.

Continuing with the figures, the system for monitoring a switchgear isdescribed in further detail, with respect to specific embodiments.

FIG. 1 shows a detailed workflow relating to an example of theprocessing undertaken to determine a fault in a switchgear. As shown at“A” an IR image of a switchgear is acquired by an infrared camera. Apre-processing step can be used to increase the image quality. This caninvolve noise suppression, compensation of optical effects, removal ofedges, etc. At “B” the hottest temperature point within the image isacquired or identified, for example 35C. There could be several pixelsthat have exactly the same highest temperature and either or both can beselected. Then at “C” all the pixels in the image that are within athreshold temperature range of the highest temperature are selected. Forexample, if the threshold temperature range is 7 C, then all pixelsbetween 28 C and 35 C are selected. Thus, the threshold value is used tocompute a range of values which are considered hot in this particularcase. The threshold is the maximum temperature minus a specific value.This value can be a fixed number of degrees Celsius or a percentage ofthe current average temperature of the image, or a percentage of themaximum temperature of the image or a dynamically changing value indegrees Celsius depending on the average or maximum temperature of theimage. Thus, the threshold can account for the influence of the ambientair temperature (inside the compartment and/or outside of theswitchgear) as well as take into account any influence of compartmenttype. The result is shown at in the following image. Optionally, at “D”regions that are connected are identified. At “E” the pixel count,number of regions, shape, and/or size of individual regions is analysedto decide whether this is a fault or not. If a fault is determined at“F” the pixel map is overlaid on a visual light image of the switchgear,for example of the switchgear compartment, to identify the position ofthe fault and/or to define which regions belong to which phase of athree-phase system.

Thus, the threshold is used to identify all camera pixels which arehotter than the threshold value. Images with a very strong hotspot willexhibit rather a small area. If there is no hotspot, the area is wide orbroad, and in ideal cases even showing the different components ofinterest as distinct unconnected regions.

The original IR image can be transformed to a new, binary image,consisting of only two colors (for example black and white), where onecolor (e.g. black) are the pixels above the threshold (the hot pixels)and other color (e.g. white) are the pixels below the threshold (thecold pixels). In general, this transformation can result in a mask forfurther processing of the IR image, for example by a machine learningalgorithm such as a trained neural network.

A very simple approach is to count the number of hot pixels, which isshown in FIG. 2 . As shown in this figures, cases with a strong faultwill show a sharp decline in the number of hot pixels as the temperatureincreases in time. The number of pixels used for determining a hot spotsituation can be derived for each scene by counting the pixels belongingto one component of interest. If the number of hot pixels drops belowthis value, the image is showing a hot spot. The number of pixels usedfor determining a hot spot situation can be also determined byexperiments or simulations or via machine learning algorithms. Thus, thenumber of pixels of a hot region, compared to a baseline for a componentcan be used to indicate if there is a fault, and also the temporalchange in the number of pixels within the threshold region can also beused, when compared against such a baseline, to indicate that thecomponent is abnormally hot and that there is a fault.

To catch more subtle faults, additional properties can be examined. Forexample, by taking the numbers and respective sizes of distinct regions,it is possible to detect even less obvious hot spots. In the FIG. 3 ,the disappearance of one of the two phases shows that there is aproblem, this is because the phase that is faulty is hot enough suchthat it hottest temperate is great than the hottest temperature of theother phase by at least the threshold temperature range.

The image (for example a transformed binary image) can be furtherprocessed by machine learning. The machine learning model can be trainedwith typical patterns showing layout of hot pixels for images withouthot spot, layout of hot pixels for images with a hot spot on a firstspecific component layout of hot pixels for images with a hot spot on asecond component and so forth. The image can be fed to the model and themodel will classify it as “no hot spot”, “hot spot on the firstcomponent or the second component for example. The training data can beeasily created for each new scene. A subject matter expert can recognizecomponents on the IR or visual camera image and create typical patternsof black and white images that would be expected for healthy images, andimages where different components have faults. The training data can becreated from the office, without the need of expensive and timeconsuming experiments or simulations. The IR image discussed above canbe composed of several individual images or sections of individualimages, e.g. from different cameras in one panel or line-up or fromdifferent time steps.

The skilled person would appreciate that rather than looking at thehottest temperature and those pixels within a threshold range, thecoldest pixels could be identified. Additionally, temperatures need notbe considered linearly and for example a logarithmic scale can beutilized or the temperatures normalization or other functions applied.Temperatures can also be represented as image, grayscale image, matrix,multiple time series etc.

While the invention has been illustrated and described in detail in thedrawings and foregoing description, such illustration and descriptionare to be considered illustrative or exemplary and not restrictive. Itwill be understood that changes and modifications may be made by thoseof ordinary skill within the scope of the following claims. Inparticular, the present invention covers further embodiments with anycombination of features from different embodiments described above andbelow. Additionally, statements made herein characterizing the inventionrefer to an embodiment of the invention and not necessarily allembodiments.

The terms used in the claims should be construed to have the broadestreasonable interpretation consistent with the foregoing description. Forexample, the use of the article “a” or “the” in introducing an elementshould not be interpreted as being exclusive of a plurality of elements.Likewise, the recitation of “or” should be interpreted as beinginclusive, such that the recitation of “A or B” is not exclusive of “Aand B,” unless it is clear from the context or the foregoing descriptionthat only one of A and B is intended. Further, the recitation of “atleast one of A, B and C” should be interpreted as one or more of a groupof elements consisting of A, B and C, and should not be interpreted asrequiring at least one of each of the listed elements A, B and C,regardless of whether A, B and C are related as categories or otherwise.Moreover, the recitation of “A, B and/or C” or “at least one of A, B orC” should be interpreted as including any singular entity from thelisted elements, e.g., A, any subset from the listed elements, e.g., Aand B, or the entire list of elements A, B and C.

What is claimed is:
 1. A method for monitoring a switchgear, the methodcomprising: acquiring at least one infrared image of the switchgear,wherein the at least one image comprises a first infrared image and asecond infrared image acquired after the first infrared image;determining a pixel in the at least one infrared image associated with ahottest temperature, wherein determining the pixel further comprisesdetermining a pixel in the first infrared image associated with ahottest temperature of the first infrared image and determining a pixelin the second infrared image associated with a hottest temperature ofthe second infrared image; determining pixels in the at least oneinfrared image associated with a temperature that is within a thresholdtemperature of the hottest temperature, wherein determining pixelsfurther comprises determining pixels in the first infrared imageassociated with a temperature that is within the threshold temperatureof the hottest temperature in the first infrared image and determiningpixels in the second infrared image associated with a temperature thatis within the threshold temperature of the hottest temperature in thesecond infrared image; determining that a hot spot exists in theswitchgear as a determination, the determination comprising autilization of the determined pixels in the at least one infrared image,wherein the determining that the hotspot exists further comprisesdetermining that the hot spot exists in the switchgear based on acomparison of the determined pixels in the first infrared image with thedetermined pixels in the second infrared image; and outputting anindication of a fault in the switchgear based on the determined hotspot.
 2. The method according to claim 1, wherein the thresholdtemperature comprises a fixed temperature range.
 3. The method accordingto claim 1, wherein determining that the hot spot exists comprises ananalysis of one or more of: a shape of at least one region within thedetermined pixels in the at least one infrared image, a size of the atleast one region within the determined pixels in the at least oneinfrared image, a position of the at least one region within thedetermined pixels in the at least one infrared image, a number of the atleast one region within the determined pixels in the at least oneinfrared image, a number of pixels within the determined pixels in theat least one infrared image.
 4. The method according to claim 3, whereindetermining that the hot spot exists comprises determining that a regionin the second infrared image is smaller than a corresponding region inthe first infrared image.
 5. The method according to claim 3, whereindetermining that the hot spot exists comprises determining that a numberof regions in the second infrared image is smaller than a number ofregions in the first infrared image.
 6. The method according to claim 5,wherein determining that the hot spot exists comprises determining thatthe number of regions in the second image is one.
 7. The methodaccording to claim 3, wherein the switchgear comprises two or morecomponents of a same type that are loaded with substantially a samecurrent, wherein determining that the hot spot exists comprisesdetermining of one or more of: a shape of a first region within thedetermined pixels in the at least one infrared image is different than ashape of a second region within the determined pixels in the at leastone infrared image, a size of a first region within the determinedpixels in the at least one infrared image is different than a size of asecond region within the determined pixels in the at least one infraredimage, a position within the determined pixels in the at least oneinfrared image is not associated with a position of the two or morecomponents, a number of the at least one region within the determinedpixels in the at least one infrared image is less than a number of thetwo or more components.
 8. The method according to claim 7, whereindetermining that the hot spot exists comprises determining that there isonly one region within the determined pixels in the at least oneinfrared image.
 9. The method according to claim 1, wherein determiningthat the hot spot exists comprises generating of at least one binaryimage, and wherein the determined pixels in the at least one infraredimage are given a different binary value than remaining pixels in the atleast one infrared image.
 10. The method according to claim 1, whereindetermining that the hot spot exists comprises a utilization of amachine learning algorithm.
 11. The method according to claim 10,wherein the machine learning algorithm comprises a trained neuralnetwork.
 12. The method according to claim 1, wherein the method furthercomprises: acquiring a visible image of the switchgear, and overlayingthe determined pixels in the at least one infrared image onto acorresponding at least one location in the visible image.
 13. The methodaccording to claim 1, wherein the at least one image comprises aplurality of images acquired at different times, determining a pixel ineach of the plurality of infrared images associated with a hottesttemperature in each of the plurality of infrared images, determiningpixels in each of the plurality of infrared images associated with atemperature that is within the threshold temperature of the hottesttemperature in each of the plurality of infrared images and calculate anumber of determined pixels in each of the plurality of infrared images,and wherein the determination that the hot spot exists comprises adetermination of a rate of change of the number of determined pixelswith time.
 14. The system according to claim 13, wherein thedetermination that the hot spot exists comprises a comparison of therate of change of the number of determined pixels with time against abaseline rate of change of the number of determined pixels with time.15. A method for monitoring a switchgear, the method further comprising:acquiring at least one infrared image of the switchgear, wherein the atleast one image comprises a first infrared image and a second infraredimage acquired after the first infrared image; determining a pixel inthe at least one infrared image associated with a hottest temperature,wherein the determining the pixel further comprises determining a pixelin the first infrared image associated with a hottest temperature of thefirst infrared image and determining a pixel in the second infraredimage associated with a hottest temperature of the second infraredimage; determining pixels in the at least one infrared image associatedwith a temperature that is within a threshold temperature of the hottesttemperature, wherein determining the pixels further comprisesdetermining pixels in the first infrared image associated with atemperature that is within the threshold temperature of the hottesttemperature in the first infrared image and determining pixels in thesecond infrared image associated with a temperature that is within thethreshold temperature of the hottest temperature in the second infraredimage; determining that a hot spot exists in the switchgear as adetermination, the determination comprising a utilization of thedetermined pixels in the at least one infrared image, whereindetermining that the hotspot exists further comprises determining thatthe hot spot exists in the switchgear based on a comparison of thedetermined pixels in the first infrared image with the determined pixelsin the second infrared image, and wherein determining that the hot spotexists comprises an analysis of one or more of: a shape of at least oneregion within the determined pixels in the at least one infrared image;a size of the at least one region within the determined pixels in the atleast one infrared image; a position of the at least one region withinthe determined pixels in the at least one infrared image; a number ofthe at least one region within the determined pixels in the at least oneinfrared image; a number of pixels within the determined pixels in theat least one infrared image; wherein determining that the hot spotexists comprises determining that a region in the second infrared imageis smaller than a corresponding region in the first infrared image; andoutputting an indication of a fault in the switchgear based on thedetermined hot spot.